Mingzhu Tang
- Artificial Intelligence top 2%
- Control and Systems Engineering top 5%
- Electrical and Electronic Engineering
- Computational Theory and Mathematics top 2%
- Renewable Energy, Sustainability and the Environment top 10%
- Topics
- Machine Fault Diagnosis Techniques (17 papers)Metaheuristic Optimization Algorithms Research (10 papers)Energy Load and Power Forecasting (9 papers)
- Partner nations
- ChinaUnited StatesGermany
In The Last Decade
Mingzhu Tang
36 papers receiving 1.0k citations
Hit Papers
Peers
Comparison fields: 5 of 83
- Artificial Intelligence 609
- Control and Systems Engineering 284
- Electrical and Electronic Engineering 247
- Computational Theory and Mathematics 206
- Renewable Energy, Sustainability and the Environment 179
Countries citing papers authored by Mingzhu Tang
This map shows the geographic impact of Mingzhu Tang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Mingzhu Tang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mingzhu Tang more than expected).
Fields of papers citing papers by Mingzhu Tang
This network shows the impact of papers produced by Mingzhu Tang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Mingzhu Tang. The network helps show where Mingzhu Tang may publish in the future.
Co-authorship network of co-authors of Mingzhu Tang
This figure shows the co-authorship network connecting the top 25 collaborators of Mingzhu Tang. A scholar is included among the top collaborators of Mingzhu Tang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mingzhu Tang. Mingzhu Tang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 3 | |
| 5 | 29 | |
| 6 | 14 | |
| 7 | 61 | |
| 8 | 8 | |
| 9 | 26 | |
| 10 | 7 | |
| 11 | 17 | |
| 12 | 4 | |
| 13 | 6 | |
| 14 | 3 | |
| 15 | 50 | |
| 16 | 134 | |
| 17 | 18 | |
| 18 | 21 | |
| 19 | An exploration-enhanced grey wolf optimizer to solve high-dimensional numerical optimizationbreakdown → | 235 |
| 20 | Modified support vector data description for fault diagnosis | 5 |
About Mingzhu Tang
Mingzhu Tang is a scholar working on Control and Systems Engineering, Artificial Intelligence and Computational Theory and Mathematics, having authored 41 papers that have together received 1.1k indexed citations. Recurring topics across this work include Machine Fault Diagnosis Techniques (17 papers), Metaheuristic Optimization Algorithms Research (10 papers) and Energy Load and Power Forecasting (9 papers). The work is most often cited by research in Artificial Intelligence (609 citations), Computational Theory and Mathematics (206 citations) and Control and Systems Engineering (284 citations). Mingzhu Tang has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Wen Long, Jianjun Jiao, Ximing Liang, Ming Xu, Shaohong Cai, Tiebin Wu, Huawei Wu, Qi Zhao, Steven X. Ding and Bin Huang. Their work appears in journals such as Expert Systems with Applications, Energy and Sensors.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.